Effectively managing, sharing, and analyzing large volumes of data in real time is essential for making informed decisions, predicting potential threats, and adapting to changes on the battlefield. It therefore represents a critical capability for military operations. However, implementing effective analytics at the tactical edge requires to address the challenges of Denied, Degraded, Intermittent, and Limited (DDIL) networks, particularly in terms of bandwidth and processing capability constraints. Additionally, implementing such a system presents other challenges such as ensuring the security, trustworthiness, integrity, and privacy of data in motion and at rest. The accurate analysis of the vast amounts of data generated at the tactical edge requires a dedicated IT infrastructure shareable designed to operate in an unpredictable and changing environment while still ensuring the availability and reliability of the data. To address these challenges, we propose a middleware architecture based on a data mesh approach, which is designed to adapt to the demands of modern tactical networks by providing a secure and efficient data-centric storage solution for (big) data. Our proposed middleware is based on a distributed domain-driven approach to serve “data as a product”, facilitating data management and analysis, and providing a flexible and robust solution for developing data-driven services. “This paper was originally presented at the NATO Science and Technology Organization Symposium (ICMCIS) organized by the Information Systems Technology (IST) Panel, IST-200RSY — the ICMCIS, held in Skopje, North Macedonia, 16–17 May 2023”

A Data Mesh Approach for Enabling Data-Centric Applications at the Tactical Edge

Dahdal, Simon
Primo
;
Poltronieri, Filippo
Secondo
;
Tortonesi, Mauro;Stefanelli, Cesare
Penultimo
;
2023

Abstract

Effectively managing, sharing, and analyzing large volumes of data in real time is essential for making informed decisions, predicting potential threats, and adapting to changes on the battlefield. It therefore represents a critical capability for military operations. However, implementing effective analytics at the tactical edge requires to address the challenges of Denied, Degraded, Intermittent, and Limited (DDIL) networks, particularly in terms of bandwidth and processing capability constraints. Additionally, implementing such a system presents other challenges such as ensuring the security, trustworthiness, integrity, and privacy of data in motion and at rest. The accurate analysis of the vast amounts of data generated at the tactical edge requires a dedicated IT infrastructure shareable designed to operate in an unpredictable and changing environment while still ensuring the availability and reliability of the data. To address these challenges, we propose a middleware architecture based on a data mesh approach, which is designed to adapt to the demands of modern tactical networks by providing a secure and efficient data-centric storage solution for (big) data. Our proposed middleware is based on a distributed domain-driven approach to serve “data as a product”, facilitating data management and analysis, and providing a flexible and robust solution for developing data-driven services. “This paper was originally presented at the NATO Science and Technology Organization Symposium (ICMCIS) organized by the Information Systems Technology (IST) Panel, IST-200RSY — the ICMCIS, held in Skopje, North Macedonia, 16–17 May 2023”
2023
9798350343854
Big Data; Federation; Internet of Battlefield Things (IoBT); Machine Learning; Tactical Networks
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2529652
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